Accession Number:

ADA434952

Title:

Adaptive Target Detection FLIR Imagery Using the Eigenspace Separation Transform and Principal Component Analysis

Descriptive Note:

Final rept.

Corporate Author:

ARMY RESEARCH LAB ADELPHI MD

Report Date:

2005-06-01

Pagination or Media Count:

26.0

Abstract:

In this paper, an adaptive target detection algorithm for forward-looking infrared FLIR imagery is proposed which is based on measuring differences between structural information within a target and its surrounding background. At each pixel in the image a dual window is opened where the inner window inner image vector represents a possible target signature and the outer window consisting of a number of outer image vectors represents the surrounding scene. These image vectors are then preprocessed by two directional highpass filters to obtain the corresponding image gradient vectors. The target detection problem is formulated as a statistical hypotheses testing problem by mapping these image gradient vectors into two linear transformations, P1 and P2 and, via principal component analysis and eigenspace separation transform, respectively. The first transformation P1 is only a function of the inner image gradient vector. The second transformation P2 is a function of both the inner and outer image gradient vectors. For the hypothesis H1 target the difference of the two functions is small. For the hypothesis H0 clutter the difference of the two functions is large. Results of testing the proposed target detection algorithm on two large FLIR image databases are presented.

Subject Categories:

  • Infrared Detection and Detectors
  • Target Direction, Range and Position Finding

Distribution Statement:

APPROVED FOR PUBLIC RELEASE